A collaborative filtering method has been proposed in which information relating to the preferences of many users is accumulated, and using information of another user whose preferences are similar to those of the users, the preferences of the corresponding user are predicted. Collaborative filtering is used for recommendation or personalization. For example, Patent Literature 1 describes an information recommendation method in which, when an arbitrary user votes on an arbitrary item, the evaluation value of the item is substituted in a corresponding cell of an item-user matrix, and the evaluation value is substituted in a cell of another item similar to the item in a pseudo manner. In the information recommendation method of Patent Literature 1, it is assumed that it is possible to recommend an item which may not be recommended because there is no evaluation value.